由于胰岛素分泌的核心作用,钾向内整流通道亚家族J成员11(KCNJ11)基因是2型糖尿病(T2D)易感性的重要基因之一。然而,该基因与T2D发育的相关性在不同人群中并不一致。在目前的研究中,我们的目标是捕捉伊朗成年人常见的KCNJ11变体的可能关联,接下来是荟萃分析。我们发现,KCNJ11的测试变体并未导致伊朗成年人的T2D发病率,与具有不同基因型的个体之间相似的胰岛素分泌水平一致。我们的结果与72个合格的已发表病例对照研究(41,372例和47,570例对照)的整合作为荟萃分析,表明rs5219和rs5215与不同遗传模型下的T2D易感性增加显着相关。然而,根据种族进行的分层分析显示,rs5219参与了不同人群的T2D风险,包括美国人,东亚,欧洲,和大中东,但不是南亚。此外,荟萃回归分析显示,病例组和对照组的样本量与合并遗传效应大小的大小显著相关.本研究可以扩大我们对KCNJ11常见变异对T2D发病率的贡献的认识,这对于设计基于SNP的面板在精准医学中的潜在临床应用是有价值的。它还强调了相似样本量对于避免高度异质性和进行更精确的荟萃分析的重要性。
Due to the central role in insulin secretion, the potassium inwardly-rectifying channel subfamily J member 11 (KCNJ11) gene is one of the essential genes for type 2 diabetes (T2D) predisposition. However, the relevance of this gene to T2D development is not consistent among diverse populations. In the current study, we aim to capture the possible association of common KCNJ11 variants across Iranian adults, followed by a meta-analysis. We found that the tested variants of KCNJ11 have not contributed to T2D incidence in Iranian adults, consistent with similar insulin secretion levels among individuals with different genotypes. The integration of our results with 72 eligible published
case-control studies (41,372 cases and 47,570 controls) as a meta-analysis demonstrated rs5219 and rs5215 are significantly associated with the increased T2D susceptibility under different genetic models. Nevertheless, the stratified analysis according to ethnicity showed rs5219 is involved in the T2D risk among disparate populations, including American, East Asian, European, and Greater Middle Eastern, but not South Asian. Additionally, the meta-regression analysis demonstrated that the sample size of both
case and control groups was significantly associated with the magnitude of pooled genetic effect size. The present study can expand our knowledge about the KCNJ11 common variant\'s contributions to T2D incidence, which is valuable for designing SNP-based panels for potential clinical applications in precision medicine. It also highlights the importance of similar sample sizes for avoiding high heterogeneity and conducting a more precise meta-analysis.